{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%reload_ext autoreload\n",
    "%autoreload 2\n",
    "%matplotlib inline\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scipy.io as sio\n",
    "\n",
    "import sys\n",
    "sys.path.append('..')\n",
    "\n",
    "from helper import kmeans as km"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         X1        X2\n",
      "0  1.842080  4.607572\n",
      "1  5.658583  4.799964\n",
      "2  6.352579  3.290854\n",
      "3  2.904017  4.612204\n",
      "4  3.231979  4.939894\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7fe4fc0cd160>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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IsgLZrgBuwCYKaJ7vxnuWN8PrcXB7k8UxjImobMzc66q99onBCYQiMtxOO5a0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\nERGRMJYxERGRMJYxERGRsD8BnttORLBA4wMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe4fc0cd3c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mat = sio.loadmat('./data/ex7data2.mat')\n",
    "data2 = pd.DataFrame(mat.get('X'), columns=['X1', 'X2'])\n",
    "print(data2.head())\n",
    "\n",
    "sns.set(context=\"notebook\", style=\"white\")\n",
    "sns.lmplot('X1', 'X2', data=data2, fit_reg=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 0. random init\n",
    "for initial centroids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2.11496411,  5.37373587],\n",
       "       [ 0.99253246,  5.01567424],\n",
       "       [ 1.40260822,  1.08726536]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "km.random_init(data2, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. cluster assignment\n",
    "http://stackoverflow.com/questions/14432557/matplotlib-scatter-plot-with-different-text-at-each-data-point"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### find closest cluster experiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 5.05274526,  2.75692163],\n",
       "       [ 2.12857843,  5.01149793],\n",
       "       [ 5.29239452,  0.36873298]])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "init_centroids = km.random_init(data2, 3)\n",
    "init_centroids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x = np.array([1, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fe4f478a400>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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53DVp0gQ3btyQPutzbOpTBwAiIiJw9uxZzJs3T+f3uvaTgYEBqlevrrWfNLZu3QohBIYO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\nmBARERERkckxMSEiIiIiIpP7f0FApkzLI51LAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe4fbff5c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6,4))\n",
    "ax.scatter(x=init_centroids[:, 0], y=init_centroids[:, 1])\n",
    "\n",
    "for i, node in enumerate(init_centroids):\n",
    "    ax.annotate('{}: ({},{})'.format(i, node[0], node[1]), node)\n",
    "    \n",
    "ax.scatter(x[0], x[1], marker='x', s=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "km._find_your_cluster(x, init_centroids)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1 epoch cluster assigning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>X1</th>\n",
       "      <th>X2</th>\n",
       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.842080</td>\n",
       "      <td>4.607572</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.658583</td>\n",
       "      <td>4.799964</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6.352579</td>\n",
       "      <td>3.290854</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.904017</td>\n",
       "      <td>4.612204</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.231979</td>\n",
       "      <td>4.939894</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         X1        X2  C\n",
       "0  1.842080  4.607572  1\n",
       "1  5.658583  4.799964  0\n",
       "2  6.352579  3.290854  0\n",
       "3  2.904017  4.612204  1\n",
       "4  3.231979  4.939894  1"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "C = km.assign_cluster(data2, init_centroids)\n",
    "data_with_c = km.combine_data_C(data2, C)\n",
    "data_with_c.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See the first round clustering result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7fe4f4718518>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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l9DCIiIgoB4oqhBAREVHpYAghIiIiQzCEEBERkSEYQoiIiMgQDCFERERkCIYQ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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe4f47182e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot('X1', 'X2', hue='C', data=data_with_c, fit_reg=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. calculate new centroid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 5.67762686,  2.83305931],\n",
       "       [ 1.94033883,  4.95015645],\n",
       "       [ 3.07010849,  0.90867247]])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "km.new_centroids(data2, C)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# putting all together, take1\n",
    "this is just 1 shot `k-means`, if the random init pick the bad starting centroids, the final clustering may be very sub-optimal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "final_C, final_centroid, _= km._k_means_iter(data2, 3)\n",
    "data_with_c = km.combine_data_C(data2, final_C)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7fe4f47424e0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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EZAmGECIiIrIEQwgRERFZgiGEiIiILMEQQkRERJZgCCEiIiJLMIQQERGRJRhC\niIiIyBIMIURERGQJm9UDICIi62h+P0b37IWvpxeOlmZUr1kN0W63elg0TzCEEBHNU5rfj6P3PQBv\nVxdUrxeaX0F50x+w9P/eAJvLZfXwaB7gdAwR0Tw1umcvvF1dmB4cgn90DAGPB+6j76Lj1jug+f1W\nD4/mAYYQIqJ5ytfTG6yAKEr49f5+jO7Za9GoaD7hdAwRUQlL1PPhaGmG5leiHiPKMnw9vXM9VJqH\nGEKIiEqU2fPR3WNeG96xCx/+tyswfvAQvJ2dkCocUNxuCIIAABBkGZLTCUdLs1XDpnmEIYSIqIDk\ncrXK6J69YQEEADydXei47XaoU8GeD9Emw+ZwQBdFSHY7JKcTFUtaUb1mddbvhSgZhhAiohTlejlr\n5PMtWNaGdx/6WVTl4sSrtmT0OrGmVFSvF4HxccjV1cELogR7bQ0WrlgOm8vFZbo0pxhCiMgSVu9P\nYby+t7MTqm8KksMB50wFINY44k1tZBoQYj1f77PPQZ3yAcLsmgFvdw9G9+xF7cYNab9GrCkVTVEg\n2eXwi4IIm8uFxZsvSvs1iLLBEEJEcy7XN/SMX39meaqmKBBkGWX19XHHEWtqI92AEBq8Am43PJ1d\nEMTZwOHr74dklyFVhO/RkWmTaPWa1RjesSts3I5Fi4JBJwJ7QMgKDCFENOdycUPPxeuHLk/VFQWq\n1xs1DiM49G97AQG3G5LTGR4cYgSEWFUeAHj7nvvgfvsoNL8Cze+HDh1l9Q3m84myDM2vQKoIf75M\nA4Jot+PEq7YknfJxLm5hD0iJ+/3vf49f/vKXmJychKZpqKurw1e+8hV8/OMft3RcDCFENOfifbOf\nq2WhxutELk81Asnsz2crNqrHDWUsuKFXWX29GRwiA0K8Ks/CVSswtu/AbOhRVeiaBtXrgc1VCQCQ\nnE7YnOVm0yiQfUAQ7faoYBcZTNgDUtr++7//G7/61a9w9913Y/ny5QCAHTt24LrrroPX68VnPvMZ\ny8bGEEJEcy7eN/u5mhIwXke0y9DdOqBpgK6bwcD4eWjFRnI6IUy6oU1NYXpoCLaKClSefFJUQIhX\n5ZkeGgrbFEwQxWAI8XjNEFKxpNVcPpvPgBArmFBpmpycxP3334/77rvPDCAAsHHjRjz44INYuHCh\nhaNjCCEiC8TqVZjLKQHj9T0ffABoGnRVBQQBms8H1ePBgmVtAMIrM7oOQJj5g6oiuK2GHvXc8ao5\nAV9EH4YjtYuCAAAgAElEQVQgQLTZzGbY0MDBgEC5sm/fPgDAmWeeGfWzFStWzPVwojCEENGci9Wr\nMJdTAsbrdz7+BAITE9A1DYIoQpzZJ2P84CHUbtwQVplRvV7oM9M3giQBCAaOyD6WeNWchcvaMDB0\nDHpoNcRux6JPnof6s89KOmarVxNRcRofH0dDQ4PVw4iLIYSILDGX3/jj3cBtLhfk6pqo3zeqGaEV\nG83vhxYImM/nH1Uguj3wdnaFvY94VZ7WSy6Gf3QMk0fehqYoEGUZlSefhNr1p6c0/niriQAwnFBc\n1dXVGBgYsHoYcTGEEFFJS3QDT9abElqx6X32OQQmJ4MNqTNbnGuKAjVimiXeipTxg4fgbG1BWV2t\nuSfJgmVtKQUIo88k2MgaXNETcLsx9LfXML7vgGVLnanwrVy5EqIo4oUXXsC5554b9rOXX34ZHo8H\nn/zkJy0aHUMIEZU447h61euF5lcg2mV4u7owumdvSr0pRsXG29kFT2dn+HSKLENyOKJeM7TKEysE\nORe3oOlT58fdHdUYtxFOvJ1d0DUN00ND5uurALoefwJShStsyfBcLHXm1FDxcLlcuPbaa3HLLbeg\nqqoKGzYE/7nYsWMHvve97+GWW26xdHwMIURU0rydneaGZAAAD8KmURL1poTebFWfD2V1tVB9U+Z0\niuR0wrmkNeHrx1st0/3k0zGvD+96HaO794T9TCq3I+DxhAUgAFC9PnO301D5XOps9UZzlL4vfelL\nqK+vx1133YXx8XHIsoxFixbhnnvuwdq1ay0dG0MIEZU0IzSEMqYzhnfsNMNH86cvCLuJRt5sg1Mh\nPthcFea26qms6IkXCDzvfxDzemQAMd6DEPF7oixDqnBGvTcgv0udrd5ojjJz/vnn4/zzz7d6GFEY\nQoiopEkOBwRZDq8i2GwYaz+I8b93mJciv80P73odE2++FVb1kCoq0j7oLV4gqDj+OIy1H4rxk+hl\nvxBEVJ5ykrnbqmgPjgcApHIH1Olp81fzvdTZ6o3mqLQwhBBRyYjVq+Bc0oqy+nqzoVOUZei6Dm1q\nKuyMltBv85rfj56nnoF/dNTcyEyQZZQ1NqZ90Fu8vpPFmy+Cf2Q06vqCVSsw+daR8LAhiKhZfzoE\nUYr6/bnY3CyU1RvNUWlJK4Rs27YNO3bsQHNzM/7lX/4FlZWVYT8///zz8b//+785HSAAvPnmm7j9\n9ttx6NAhlJeXY926dbjxxhtRV1eX89ciotyY6+bFeL0KH/63K1AREQKgqeYKl1DGt/nRPXsR8Hqh\nBwIzu5QB+vQ0pgcGUNaY3p4LifZEibWK5p2f/DcUtwe63z+zf8koKk74MKpXrUT1qpXofvJpeN7/\nABXHH4fFmy+CzeWa02kQqzeao9Ii6Loeo/YX7X/+539w++2345RTTsHg4CBkWcYjjzyCJUuWmL+z\nfPlytLe353SAfr8fH/vYx3DZZZfhiiuugNvtxjXXXIOFCxfi3nvvTfjYTZs2AQC2b9+e0zERUWLx\nVoTks3lxeMdOdG19OvyirqGq7SNQRkfhHx6BvbYGNTP7cvQ882zU7xpTLZ7338fogXaok+5gCJkJ\nLKIs48Rr/r+UNhfL5j3oagBT/QPBKSRBgFxTg6pTTgagw9fbb/5+vj/TeLg6hnIl5UrI448/jh//\n+Mf4p3/6J/j9ftx00034yle+gq1bt6KmJrjZjxDjm0W2pqamcN111+Giiy6CKIqorq7Gueeei0cf\nfTTnr0VEuWFF82JUT4KuYXpwEAPbeswQIXR2ARBwwpVfC28A1TUE3B6M7m+HIAC+3j5o09NmFQQI\n7pIqVy/E9MAggPzciI33oPp8wSrMDE1RMHnkbQgC4k4hzSVuLU+5knII6e/vNysLdrsdt99+O7Zs\n2YJvfetbePjhhyGGrFPPpaqqKmzevNn887vvvotnnnkGF1xwQV5ej4iyZ0XzYmRPgur1Qp0KNmwa\n26zrMzfz8YOHwqZCAm53MICIIlSPO9gHYjACjC34n0tvZyeGXv0rRna9HlaVyMUyVUdLM3RNgzI6\nFjzPJuS9aH4/BE2Drs8cpjfz31w2hFIxSzk51NTU4IMPwpeU3XXXXRgeHsbNN98MAEhxZicjvb29\naGtrwwUXXIDly5fjqquuyttrEVF28t28qPn9GN6xE91PPo3hHTuh+f3BJtTFLSG/owRv1BFfkDRF\nga+n1/w2b/RVCAKgetxQxoNnyYiyDMFmgyCKwRCjaQh4vPB0duOD/3kcY/sOAPpsWDGqEtmoXrMa\nNocDemgIQjA8aVPBpcbK2Fhw07KZ3zE+01ifCVGhSzmEnHvuubj66quxc+dO85rT6cRDDz2EnTt3\n4qqrrsprCGlubsahQ4ewbds2vPfee7j++uvz9lpElJ3IQADkrnnR6Dfp2vo0jr0W7KE4et8DAIAT\nr9qC1osvQt0ZG1D/j2dDrl4YNU0synJUGCprbMD04BD8I6NQ/X7ogQA0RYFcvRD2ujpI5eUQHQ6U\n1ddDEEVoihLcst3rDXuebKsSot2OhSuXwV5bEwxBkhQMQLoOUZIglZcBCIYS1es1P9N4n0lkEGFQ\noUKTcgj55je/iVNOOQV/+tOfwq43NTXh8ccfh67rCITMYebLkiVLcN111+G5557D6Oho3l+PiNJn\nrPwwAkHrxRflrIEyUb9JaHVjyb98HpUnnwRRls3fE2YOjYsVhnRdDx5QZ1QhdB3+0THYnA6U1dfB\nXlNjToEYz6nNnKoLXYPqccPb2Zn1zd25ZAlsrko4FgfPmTHCiFy9EGUNDbBXL4StogJVp55ifqaJ\nPhNDqkGFaC6l3BPy3nvv4c4774z5s7q6Otx333148MEHczYww86dO3HzzTdj27Zt5jVBECAIAuSQ\n/7gQUWHJV/Oir6c3eNMPOQtGcjqjqhCi3Y6TrrnK3AYd0FG9bi1q158eFYamBwYhVVQEN/0K6cWA\nqkILKGj554vQ9/s/mpclpxMBjweiXZ5pgB2CDsDT2Q1v99NZ9YeELoGVKlzQdUD1eGCrCO7UKlW4\nIFUAtRvXm8+fSg8OdzqlQpRyJeSSSy7Br3/965g/GxkZwVe/+lX89Kc/zdnADG1tbXC73bjzzjsx\nNTWFkZER3HfffVi7di1cEeclEFHpMqYSPO+/D19vH6ZHRhHweOAfHcP04FDM/TtEux31Z5+Fk7/1\nTZz8rWtRf/ZZMYOBo6UZeiAwuzW6IACCAEGSoHp8EG02OBe3QNc0BNxuKOPjcLYuxuLPfw7O1lZI\nFRXmVA2QvD8k0bRIZBXpuMv+BQtXrTC3igeip7ZS6cHhTqeUKz09Pfj617+O9evX45xzzolboEhF\nypWQ73//+/iP//gP7N69Gz/84Q/hmDk5cufOnbj++uvR0tKCZ555JuOBxONyufDzn/8ct9xyCzZu\n3Ain04kNGzbg1ltvzflrEVF65mq/iNB9RwLuydmbts0GQRBibXSeluo1q+FY9Bwmx8dnL870kmh+\nP0Z378Hx/3oZ3rrz/yEwPg7JLkObnsb4vgPBU24jKgxA/Jt7KgfAGVUk4/N1trairK4OksMB55JW\nM4AYZ9+UNTbA0bwoag+RdIMKUSquvvpqLFu2DC+99BKGh4fxta99DXV1dfjXf/3XtJ8r5c3KAOCd\nd97Bt7/9bUxPT+O//uu/8MILL+Chhx7CFVdcgWuuuQbSzDK4QsHNyojyZy43JAvdiEwZHUXA7Q6u\nYCkvh62iApLTifqzzkhrO/VIAbcb7Tf8X0z19gOCYK4+EW02yNXVKKuthTrlA4CwqaDq09dhIuQM\nGkPrxRfFnOaIualajN9P9PkCiPqZo7kJNevXYXpgMGYgzObvi5uTFbZpRcVbH4xAliScvGQhJCk/\nW2YAwMGDB/GFL3wBO3fuNGcjnnjiCfzyl7/EH//4xySPjpbWtu0nnHACtm7dijvuuAMXXnghamtr\n8fDDD+P0009P+4WJqLjNZY9BaFVBtMvmVIlot5vH2Gf7jd7mcmH57beh47bb4f2gC+rUVHB5rt0e\n7Dnp74co26B6vLMn13qA8faDcLa2wtfbN3PSrhc2pwNaIADN74+6Wac6LZKs2TTyZ77ePog2W9wg\nlmj7+FCRgWPBsja8+9DPElZuyDpHu8fw8LN/h286+M9kTZUDX79oGRqqnXl5vcOHD6OlpSWsHeK0\n007De++9B4/Hg4qKirSeL+0D7Pr7+7Fv3z40NTVhZGQE+/fvZwghmofMm2ZEk6i3syvnISQ0YEhO\nJ0S3xzyMDoi//Ne4oXo7O6H6psKmM2LdQG0uFz5y8004et/9GDv4d/P0XEEUIcoyVI9nNoDMUH1T\nqFm/DgDQ89QzwVkcQUDPM89idPeeqJt1qtMimfRwJOvvSNYsHKta0vvsc8EKUEhPChtaC4Om6fjV\n82+ZAQQARiZ8ePrPR3HlRcvz8ppjY2OoqqoKu7Zw4ULzZ3kNIc8//zxuvPFGnHnmmXjkkUdw9OhR\nXHvttdi5cyf+8z//kwfKEc0jjpZmc2VIaGVgbH87Wi78TE6/JYcdmiaIKGuoh+Qox8IVK+KGCvOG\n2tVljlGQZZTV1yf8Jm/cqL3d4Td0yekEdA3a+Ox/8IWZkDLV2wfV54MyPhGs1MzwdnWh8/EnYHO5\nzMpDqgfAZdLDkW01KFb1xdffD8kuh20XD7ChtRAMjnoxMuGLuv5W5yg0TYco5v4olViMro5Mjm5J\nOYT8+7//O5588klcf/31+PKXvwwAWLlyJZ5++mlcf/31+PSnP4077rgDZ599dtqDIKLiU71mNXp/\n/4ewyoAgywj4fCl9S45V9g89kj7yz+keWW/cUFXv7PSJsclXsm/ysYJCxZJWLFi1Al2/+o1ZhZGc\nTghCMHj5+vuhejyABxDdHpTV12F66BgGX34Fkt0Oza+gvOkPWPp/b0hpWiRZWMnHSbaxgoUoy9D8\nCqSIL7hsaLWey2mHKArQtPDWzkqHnLcAUlNTE7VH1/j4OARBQHV1ddrPl3II+ctf/oJHH30UK1as\niBrQz372M9x7773YsmULDh06lPYgiKj4iHY7Fq5YgeljI+E3ZVFM+i05quyva3jv4UcgVVRAEMVg\nb8XDj8DmqjCnAYzqRapTAMYYzA3FjNeeCSSJxhivfwIAxvcdCLv5S+V2BLy+4HRNyGv4R0eDq3gC\nAahuT/BMmPFxtH/3Riy/49ak7yNZD0cqQSZdsYKF5HTC5iyHOjW7jDhXu99SdlwOGaeftgg7D/WF\nXT9nbWveXrOtrQ29vb0YGxszp2Ha29txwgknmKtm05FyCHn66afjphxBEHDNNddg9Wr+Q0k0nziX\ntJqNoaGSfUuOLPurXi+U8XFAEGBzucw/C6JgTgNEVi+SrdgwxiDaZcAz+9pGH0myMcbrnwi9+Zc1\nNmBk1+uY6uuAINsgyDboSnDnaG3aD4gidFUNHkY3U7Ke6utDx2234yM33xQ3NES+t+ZPXxD1u5lu\nBpfoc4tXAUq3CkVzZ/Omk1Ff7cC+t4Zgk0RsXNaE0z+yKG+vt3TpUixfvhx33XUXvvvd72JgYAC/\n+MUvcMUVV2T0fCmHkFTKLGeddVZGgyCiwuRXFezrO4TeiQE0VzViVVMb7NJsz0Oq/Q2RIqsQRrXC\nqFKY/xsxDTBb3Ui+14Y5tq4us5HV6OHI5pt86B4eR+6+B2P7DkD1+QBBgFheBnnhAmhKAJUnnoDJ\nt9+GMjE5uxX8zCZoU30DcQOVEWxyfUKv5vdjeNfr6HnqGQS8PrNqFfrciaovbEItTJIo4Jy1S3DO\n2iVz9po//vGP8YMf/ABnnXUWXC4XvvCFL+ALX/hCRs+V9uoYIpof/KqCn+x+FL0TszfDXd37ceW6\nS80gkuqyz0iRVQijWmFUKYypjdAmz9DHpbI8OHRs3s4uqD5f0tUx6Rj622sY2bV7tsqh69C8Pugu\nFxYua8Px/3oZ9l/77fBt4HUduiBAtMtxA1XA7Ybq8aCsod6cisp2NYrxGpNvvQX/6FjwdTwelNXX\nx/zcGDgokcbGRjz00EM5eS6GEKISlayKkUzwsf1h13on+rGv7xDWL15lXsvkphVZQZGcTsiaHlyB\nAmMlyuyfgfAKS6rLV42xpTK+dDfkGnzhT8EAEkGUZ8OPXF2NgNcHPaR5V5QkSE5n3EAVekJv6IqU\nbFajGK8R2h9jNOnaXC6udCHLMIQQlaBUqhjJ9E4MxLzeNzmY9fhiVVCSrY4JDQW53oI8lemdSKpv\nZmlkxKbTyliw0uDt7IQ2NQWby4WA2x2ckhEESE4HHC3N0AIBdD/5NLydnYCumVUPowoUORWVzWoU\nI2RE9scY015c6UJWYQghKkGpVjESaa5qjHm9qTL6oLhMxKqgJPuzIdNelHgy2f21alkbPO9/EHVd\nsEkY3vU6xvYfNKc+BEEAZBk2pwO1Z2yA+5138f7Dj0C0y9B1HarHa06/hJ3Qm4P3BsyGjNCN3oBg\n4OFKF7ISQwhRCcpFFWNVUxt2de8PCzPNVYuwqqkt6/FlK9NelFCh0y/ezk7ommaegmtINE2x5JKL\nMbj9z8G9QWYINhvs1dUY3b0HAZ8PgiwHp2IEAdB1lDU2wn30PXjeez/4AE/wMRBgTr8IoojqVSsT\nngOTrtDQVtZQH3wthwMt/3whatefzpUuZBmGEKISlIsqhl2SceW6S7Gv7xD6JgfRVNmQdl9JPmXT\nQBk5/aJ63FDcwUbN0CCSaJrC5nLhQ1+7HB/84pfQpv0Q7DJEexmUiUlMDw0BAMrq683N0kRZRlld\nLcYjDrvTAwHICxeg8pST4VyyJC9LYHMR2ojygSGEqATlqophl+SUp2+KSeT0i+R0Qpl0wz8yEjwY\nT5ZRefJJSacp6s88A+P7DsDT2YXpoSEEJiYgyjKmh4cR8HhRVl8fto+KeQZNxPPoSiDlBtpMcdUL\nFSKGEKISVOhVDKtFTrPoOgABgKpCkKTgIXTQYzwynFFh6Hz8CQy9/CpEV4W5okf1eM3VJ8BMX8e6\nNfB0diPg8YStmClvamRfBs1LDCFEJapUqxi5EDnNonq90JUA5OqF5rJYX29/SntziHY7bC4X5IgN\nHcsa6uFsbYVzSWvYtu8ju16H6vVA9XgBAOUtzWj8+D+h99k/cJqE5h2GECKadyJX14SefRMq1f0z\nYvaOCCJqN64PCzGa349gyUWAYLdDsNmgjIyi99k/RJ2RwyBC84GY/FeIiEqLMY3SevFFqDtjAxr+\n8eywHUoNqe6fUb1mNZyLW8KuxVr6OrpnL3y9fbC5XLBXV0MQBCgTE1C9XvN3jKXBRPMBKyFENC+F\nNmpqfj/8I6MZ7zuS6uqTqDNzkpyRQ1SoXn31Vdxwww3YsGED7rrrroyfhyGEiOa9XCxhTWX1SdSZ\nOUnOyCEqRD/96U/x1FNP4fjjj8/6uRhCiKjkpXIuzFwsYY11Zk6iM3KIUuH1+9Bx7ChsooSl9Sfl\nfRVceXk5tm7diltvvRV+vz+r52IIIaKSlsm5MPmSypk5XB1D6Xjr2Dt49MAzUNTg1J7LXoGvrvk8\nFuXoeIVYLr300pw9F0MIEZW0TM6FyadUzswB0j/Vt5iU8nubS5qm4enD/2sGEABw+z149s0X8W/r\nvmjhyFLHEEJEJS1ek2chN38WUvUm10r5vc21Ie8wxqcmo66/N9oFTdcgCoW/ALbwR0hElIV4TZ6F\n3PyZqHpT7Er5vc21yjIXJFGKul5VXlkUAQRgCCGiEpfqHh6FpBirN6kq5fc215yyI+auyB/70EYL\nRpMZTscQUUkrxhNki7F6k6pSfm9WuOCUTWioqEV7fwdskg2nt6xAW+OpVg8rZQwhRFTyiu0E2cil\nvEDhV29SVcrvzQqiIGJD62psaJ27z2/58uUQBAGBQAAA8OKLL0IQBBw4cCDt5xJ0XU9+VGSR2rRp\nEwBg+/btFo+EiCg9pbyCpJTfG6WHlRAiogJUbNWbdJTye6P0MIQQUcnjN2+iwsQQQkQlrRD2pWAI\nIoqNIYSISprVO6YWQggiKlTcJ4SIiprm92N4x050P/k0hnfshBZxoJbV+1Jwcy6i+FgJIaKilUqV\nwep9KawOQUSFjJUQIipaqVQZrN4x1eoQRFTIWAkhoqKVSpXB6h1TuTkXUXwMIURUtFKtMli5L4XV\nIYiokDGEEFHRKpYqAzfnIoqNIYSIiharDETW6O3txW233Ybdu3dDlmWcffbZuPHGG+FyudJ6Hjam\nElFRM6oMizdfhNqNGxhAiObAlVdeiQULFuDll1/GU089hbfffht33HFH2s9TFCGkt7cXV111Fdav\nX4+zzjoL3/ve9+B2u60eFhERkeX8Y2MYevVvGN6xEwGvN++vNzk5iWXLluHb3/42ysvL0djYiAsv\nvBC7d+9O+7mKIoTkKnERERGVkrH2g+i49Xb0PPM7dG19Gh233g5vZ1deX7OyshK33norampqzGu9\nvb1obGxM+7kKPoTkMnERERGVCl1V0fPUM9BVzbym+qbQ87tn53QcBw8exGOPPYYtW7ak/diCb0w1\nEleoTBMXERFRqZgeGoIyGd2a4HnvA+iaBkHMf51hz549+MY3voHvfOc72LAh/RVgBV8JiZRN4iIi\nIioVtqoFEG3RtQR7TfWcBJA///nP+PrXv44bb7wRX/ziFzN6jqIKIXv27MFXv/rVjBMXERFRqbA5\nHaj/x7Ojri/6xMfz/tp79+7FDTfcgHvvvRef/vSnM36egp+OMfz5z3/Gd77zHdx0001ZvWEiIqJS\n0fSp81HetAhj+/ZDtNtRc/o6VJ5ycl5fU1VV/OAHP8D111+PjRs3ZvVcgq7reo7GlTd79+7Fli1b\ncPfdd6f1hjdt2gQA2L59e76GRkRENK+88cYbuOyyy2C326HrOgRBMP9327ZtaGpqSvm5Cr4SksvE\nRURERNlZu3YtOjo6cvJcBV8JySZxsRJCRERUuAq+EpLLxEVERESFo6hWxxAREVHpYAghIiIiSzCE\nEBERkSUYQoiIiMgSBd+YSkTx+VUF+/oOoXdiAM1VjVjV1Aa7JFs9LCKilDCEEBUpv6rgJ7sfRe9E\nv3ltV/d+XLnuUgYRIioKnI4hKlLBCkh/2LXeiX7s6ztk0YiIiNLDEEJUpHonBmJe75scnOOREBFl\nhiGEqEg1VzXGvN5U2TDHIyEiygxDCFGRWtXUhuaqRWHXmqsWYVVTm0UjIiJKDxtTiYqUXZJx5bpL\nsa/vEPomB9FU2cDVMURUVBhCiIqYXZKxfvGqtB7DZb1EVCgYQojmES7rJaJCwp4QonmEy3qJqJCw\nEkJU4HI5fcJlvURUSBhCiApYrqdPuKyXiAoJp2OICliup0+4rJeICgkrIUQFLNfTJ1zWS0SFhCGE\nqIDlY/okk2W9RET5wOkYogJm5fSJX1Wwq3sfnjm8Dbu698GvKnl/TSKaX1gJISpgczV9ErkC5yMN\np+Dhvb/mfiJElFcMIURZyHT5bDqPy/f0SawVOM8deQnTgWkIEMxrRkMsp3KIKFcYQogylOny2WyX\n3eZ62/VYK3AGJodgl2RU2J1h17mfCBHlEkMIUYYSLZ9NVC3I9HFAdIDRdB3PHXkJyxtPReuC5owC\nSawVOHZJhqIFoq5zPxEiyiWGEKIMZbp8Nptlt6EBRtN1HPMOw68GMOodQ4XdmVHfRqwVOA7ZgRq5\nDNMBf8jvcT8RIsothhAqKXN5Qmymy2dTfVys9xIaYHyKD341WK0wqhaZ9G2samrDru79YdWZxQua\ncPnqS/D3wbe4nwgR5Q1DCJWMuT4hNtbNO5VqQSqPi/VednTtRXX5Aoz6xmGX5LAqhSzO/qucbt9G\nohU4bEIlonxiCKGSkW2vRaIKSryfZ7J8NpXHRb4XTdfR3n8YTtkBRVPgUXwQIUDXdZTZZDjtDvN3\nM+nbYOAgIiswhFDJyLTXIlkFJdnPM7l5J3tc5Hsxpl5kMQCn7ADggw6gpmwhymx2cyltskrMXE5X\nERElwxBCJSPTHo1kFZRsKiyZinwvwd1Kdbj9Hmi6DkEQIAoCbKINnzzpHOzr/ztGfKPQNBW7e/Zj\nXcvKqHCRznQVwwoRzQWGECoZmfZoJKugJPt5Pm7Yke/FJtoQ0FTouh78BR3QBAFeZQp/evev6Jno\ng18N4F10oX2gA7t72vGN07+UcIon+N6iw1SqYYVBhYiyxRBCJSPTHo1kFZREP89XM2zkexmfmsCL\nR1+Foofv3eEPTJsBxLymBvDO8PtR4SI0TOnQ4fX7oGgKdnXvD/ucUgkrc90ETESliQfYUUkxei0+\nu/QTWL94VUo3xFVNbVhU2QCP34tR3zg8fi8WzQQY4+fxDpGLd8Pe3bM/68PfQt9LVVklFpZXQRIl\niIIISZQgCRIULfbzKpoS1QtjhCkdOoY8wxidmoDb78Pbx97FT3Y/ao4xld6aREGFiChVrIQQhRAE\nIepaogpLrBu2puv4XccLEIXZjJ9NlcCvKvAoXihaADZRgqZrwEwjao2zGooagF+dCHuMLMpRvTDG\nFM/bx941Kyd2yQaH7AirdKTSW5PNhmtERAZWQqhkpXoU/b6+Q+ifHESF3YmF5VWosDvRPzkY9q0+\nXoUl1g3bp/jgU6bCrmVaJTCmPdr734SiKdB0DaIgokJ24ISaJbjpo9fixNrjYZdmv0/YJRtOqD0+\nqhfGCFMn1X4ILrsD1eVVqHPWQpwJXkaASFT5mf1z9PvW9GDjbDbVHyKaX1gJIcvks7ExnZ6FeNWM\n17v3Jx1brGbYcrncvLGHyqRKYEx7iIKAOmctfEqwj+Os407H59r+D+ySjG+c/iXs7jmAPb0HIQBY\nvuhU2EQZz721PWrsdknG+tZV6J2Mfs9GpcMuybh89SX4bcc2fDDWg+MWtuBTJ28K+7v6SMMpYe9b\n03V4FC8ODrxpLhdmjwgRJcMQQpbId2NjOstqI7/VG2eyeBUv3jr2LryKFw5bOT637AJsbF0bNr5Y\nU3oA4RYAABp3SURBVDUBTcXv33wxakyZbCIWGpBEQTBPtXXZKwAAu7r3mcHgynWXAoD5uRrNp0/+\n/Y/47NJzzWW7yVYR+VUFD+/9tfnzgwNvYkfXXlTITjNc7ereH7atu9vvCQsgwbHndxkzERU/hhCy\nRL733kinZyHypuxTghuBefw++AJT0HUdHr8PP9vzBPb1HY5a+mowls+uWHQa9vQeTHupcCzx+jPq\nK2pjhrg1zcvMADLkCR5uh6kJ/Kr9d3jh6CtY1nAqmqoasGLRUkDXAUHAmuZlWNeyIu7qGK/fh/Gp\nSYiYDUG9E/34++Bb5t/VM4e3hQUQA3tEiCgRhhCyRD4aG43pna6xXrw71mmeseKQHeY3+FjViMhq\nRud4D44cew8jvrHZfTkAKKoatfQ1XkUn0eFv6UxDxataAHrMEAcEx+v1G4fb6dB0DcPeUYz4xjHk\nHsGUGuxXqa+oNYPDupYVIc8T/ndjrMCJXIkT+ndlhCVN12d2d1Vgl2TUV9TEfF9ERABDCFkk091N\nDZE38o80nIKH9/4a3eN9M8fbzzZxehQv6py1WLygKW41InQb9V3d+3B48EhYAAGCK2cil77Gq+iE\nVgkix53ONJQRkIyeD+g61jS3oW9yMGyvD1kMnh9jhIpgYNAR0NSZ1TSAoOsYmxqHIIgQBAFevw8V\ndmdUBSry70YWZQC+mf+dFfp3taqpDTu69qK9/3DIyb4Kdve0x9y9lYgIKJIQ8uqrr+KGG27Ahg0b\ncNddd1k9HMqBTHc3BWLfyJ878hKmA9Mhx9sLEAURDrkckiBh+aJTzUbOVMb2R9dLmJj2GIUFCIIA\nAULU0td0KzqZTkOFTu/0vjkAWZIx6BmGYm5S5oNH8eKTJ58zM5Xkhabr0HUdAgToM29Egw4RwWuK\nNrvBWeh4I/9unHYHNOhwyLOH5EX+XdklGetaVuCd4fdhlwKQRRucdoe5yoh9IUQUS8GHkJ/+9Kd4\n6qmncPzxx1s9FMqhTHc3BWLfyAcmh8zD5mYJkAQJC8ur4LJXpPxt3C7J+M5ZW3DHq/fjvdHO4Fkt\nEFBmk6OWvqZb0clkGirW+x31jkFV1ajftYmSWTl5ZN9WuP1e6HpwSsY4b0bXdUAAZHH2X//Q8cb6\nu/lIwylxp5cMg+5jZs9Iqu+NiOa3gg8h5eXl2Lp1K2699Vb4/X6rh0M5lOkJtLFu5HZJhqIFYJdk\neBSfed240UaGgmR9GS67Ez/46DfDlr6ubm6LmlpIt6KTLLT4VWXmNdsBHVjTsgx9E9E3cUVTIIki\nJAiArgd3UhUl7O09hHUtK3HmkrUAgCfafwe/qsAXmDKnZUQxePCd0+6IO95YfzfJ/q4i35sxXdQ5\n1oNd3ft4tgwRRSn4EHLppZdaPQQqMLFu5A7ZgRq5DD5lGh7FC78agF0K3mgjb7Kp9mXYJRlnLllr\n3tBjSbeiExpajJt0uVyOgBaA2+/FT/f8Cgf6D2M64Ieu63ijpx2tC5uh6brZXBts/pxGQFchQICq\nq4AarIIcmdmC/cp1l2JdywpzGmchquD1++CQy/GpU86BTZQx5BlOON5093GJfG9DnmEAQPdEP3oP\nb+O+IUQUpeBDCFGkWNWHxQuazBUp3eN98AWmUG4rR+tMM2omp8mmKlbVIPQG3uCqA6Bj0D2M5qpG\nXL76EhzoP4zfdjwPABAg4Pdv/gnPH30Fw95R+JQpsyl2WvWjc7wHxy9shaIq0KFj1DcGDRokUYQa\ncrKuKIhw2sO3YM90yiuTfVxCA9mu7v0zoWd2ZRL3DSGiSAwhVHQSVR/WL16V9CaXTl9GJru6+lUF\n97/+S7wz/L45FSKJEupntkg39vOQBDGsh2JgcsjclyRUQFVR66zGupYV+G3H81C1YC9IaPgQBAEO\nW7m5OsZ4L5lOeWUa1IzX650YiHp86LiIiACGECpSmd5cgdSbSTPd1XV3zwFzqaqma1A1NbgkVvHC\nZa8I288j8j15FG/UdUEQIAkibKJkBhf/lHFgnQBBCAaR0DFlsjtrqGz3ccl2CTYRzQ88wI7mnVQO\naAMyP65+T2+7uVeGUa3Q9WD/hyHW7qIO2YE6Z03YSb6CIKBMkrG6uc0MBg7ZYR5YJyC44sXof4n3\nXtKVbYhI9TMmovmNlRCad1JtJs24GhBS5BAEYfbPIbljdXMbdCCqr+WyFRfh/7323+gZ7wMEwGlz\n4MS6D2Fdy0oz/EQeZrexdQ1OrP1Q0kbTdGSyj0vk1FWiXWOJiIAiCCHLly+HIAgIBILfLF988UUI\ngoADBw5YPDIqZqlM52RaDVjTsgz7+/8OvxqAKAjQgqtooWs6PH4vTqg9HutaVprBIvIm/d2zvxE8\nwXa0G8dVL8Znl54XdfCccZhdc9UifGH5Z3N+c0931U+iqav1ixk8iCi2gg8h7e3tVg+B5ql0qgGR\nq2HaGk/FeyOdmFYV+Gb2LbHb7GGPibeqJvQE20MDb2HEN272oWSy2iWT5tp444v3fPk+kJCISlPB\nhxAiq6R6049VBVhU2YDPL/809vYewpFj74ad65JoK/NkN/N0G3Izba5N9/ma41SHuBqGiBJhCCFK\nIJWbfqzg0D85CJtow+KqJvSksVQ116cLZ1uhcPu9+G3HNrw/2o3jqxejdUFTzOercSyI+XiuhiGi\nRBhCiJJINp2RKDiksxx4X98hdE30wuP3hm3yFev3U5VNqHH7vfjuC7dhfGoSAPDmsXcgizbUOmtg\nE8MX1jls5WiuWpTRgYRENH8xhBDFETzHZT9+2/ECppQpc0olcjrDCBrGNuyKpkAWZdRX1KbUVxI6\nxaFDh0fxwqN4UTezuVk2N/N0m2tDA9fbI+9hfGoCoct6plU/xqfGUeusDnvc4gVN+D+nfjyj3VmJ\naP5iCKGCk2kjZa7H8JPdj+LtY+9idGZjMI/iRX1FbdR0xqqmNuzo2mtuUAYAdil4EN26lhVJ+0pC\np0wECKivqIXX70PrgiacvnhlVu8/3eba0H6P3skBBDQVNlGCEUREQQjbxyT0+bLZQI6I5ieGECoo\nuW6kzJQRDPyqEjK2ALx+HyrszrDpDLskY13Lcrwz/D7sUrAK4pAdYQ2oiW7OvRMDUVUUp92B1gXN\nWd/U01lRE9k/UibZMR3whx2eBwg4c8k6nFp/AiseRJQ1hhAqKIWy1NPopQhupT6706miBSsdkdMZ\ng+7hsHNgDKn0XjS46jDkGTarKIDPrLpkK52qUmT/yILyBfAo3uCur4JxrRL//JFPwhXjvRIRpYsh\nhApKrleHZMropXDIDngUrxkQZNEWczoju23Oo8+RSXw9tXCRblUp8j3YRBHNlU1ocNVAUQM4bmEL\nPrv0PAYQIsoZhhAqKPk6+CzdPpPQXgpji/RyuRyfXfoJrGtZEfXYTLY5Nwy6h8O2YTemc4Y8IzHf\nQ9d4L9oH3sSUMm1Ok8QKF+lWlWK9hyULm+d8KoyI5g+GECoo2dzM48mkzyTd3Ukz3c0UCAYvYxv2\nUKHBy68quP/1X+Kd4ffh8XsxpfpRJsmor6iDKAgxw0W6VaVs3gMRUSYYQqig5ONGmGmfSTrbltsl\nOePVIakEr909+83VN6qmQtM1+HQNXr8XrrIKANHhIpOqEle4ENFcYgihgpPrG2Eu+0zysXonleC1\np+eg2ZdinMyr6zq8AZ8ZQiLDRT6qSkREucQQQiUvl30m+Vq9E+8wO6PiMuwbRbBRVZg5mVcIrlqZ\n6V2NFS7yPb2S6/1cCmF/GCKaWwwhVPJyWRGYq9U7kRWXyWkPNF2DKIgABNhECaIgYsWi07Bhyeq4\nN+x8Ta/M1cF4bIolKm0MIVTyclkRyNfqnUiRFZcKuxNexQebJEESJMiiDSfUHo8tp3/Jkpt0ritC\nhbI/DBHNLYYQmhdyVRGYqz6LyIqLKAS3c29d0ITWBc2Wr1zJdUWoUPaHIaK5xRBClIa5WsYaq+Ii\nCgJOX7zS0spA6F4lHr/XPNTPEKsilEqvx1xVmIiosDCEEKVpLpaxFuLKltC+DU2fPe23vqIWAmKf\n9ptqr0chvl8iyj+GEKICVIgbh4X2bYiCYO7y2lLV9P+3d/cxVdd/H8dfR/EuSNQs5GIzp64LuBQj\nU3Dh5k1W64a8m6XLeYt3ibOESTLNLE1LV94snatFW6yNbD8hNShnsyxb3rTkEs1iVgqKxQELu+oo\nnOsP5SiBtwfO+wvn+diY4/s9h73Y8Hxe38/n8z1HCVf5tN8b3evhxN8XQNOjhAABdDO3oTrtjcMa\n2qcS2vY2db/Gp/3ezF4Pp/2+AJoeJQQIECfehnozpaihfRs1Xq+qPOf0n6L8Bp/PXg8A10IJAa7Q\nlG+Y5bTbUG+2FP1730btvpDCsqO+zan/fj57PQBcCyUEuKSpZyoCeRvqjZSpmy1F/963UeU5V6eA\nNPR89noAuBZKCHDJ1QblfSXfK6RVa79nRwK1NHGjZepWStGV+zb+U5Rfp4Bc7fns9QBwNZQQ4JKG\nBmWvvNp6pECtXa18x251diRQSxM3OsPhbylivwcAf1FCgEsaGlT/8vyfpItvm17rVvdxBGpp4kZn\nOPwtRU7f78EH4gHORwkBLmloUG3fpv0NLTnciEANijc6Q+FvKXLyfg8n3okEoD5KCHBJQ4PqhZoL\n+vjoznqPvdklh6YaFBsqNjczQ+Hvfg2n7vdw2p1IABpGCQGu8O9B1VN9XgdK/9fvJYemGBSvVWyc\nOkMRKHwgHtA8UEKAa2isJYemGBSvV2yC+YqfTbNA80AJAa6jMZYcrjUo3upeEa72r87pm2YBXEQJ\ngYlgu3PhaoPi/9z137e8V4Sr/atz8qZZAJdRQhBwwXjnwtUGRX/2inC1f21O3TQL4DJKCAIuWO9c\naGhQ9GdJxQlX+8E2owWgcVFCEHDsZbjM3yUVy6v9YJzRAtC4Wl3/IUDjYi/DZfGRffRfHbvVOdZc\nllSuNaMFADeCmRAEHHsZLnPCksqtYkYLgL8oIQi45jzwNoXmuoGSGS0A/qKEwERzHXhxGTNaAPxF\nCQFwS5jRAuAvSgiAW8aMFgB/OP7umJKSEs2cOVMJCQkaNmyYVq9ebR0JAAA0AsfPhKSmpqpv377a\ntWuXysvLlZKSoq5du2ry5MnW0QAAgB8cPRNSWFioY8eOKT09XaGhoerevbumTJminJwc62gAAMBP\nji4hRUVFioqKUlhYmO9YbGysjh8/rnPnzhkmAwAA/nJ0CamsrFTHjh3rHOvUqZPvHAAAaL4cXUIa\n4vV6JUkul8s4CQAA8IejS0iXLl1UUVFR59jZs2flcrnUuXNno1QAAKAxOLqE9OnTR6WlpXWWXg4d\nOqRevXqpQ4cOhskAAIC/HF1CYmJiFBcXpzVr1qiqqkrFxcXKysrShAkTrKMBAAA/ObqESNLatWtV\nVlampKQkTZo0SaNGjdL48eOtYwEAAD85/s3KIiIitHnzZusYAACgkTl+JgQAALRMlBAAAGCCEgIA\nAExQQgAAgAlKCAAAMEEJAQAAJighAADABCUEAACYoIQAAAATlBAAAGCCEgIAAExQQgAAgAlKCAAA\nMEEJAQAAJighAADABCUEAACYoIQAAAATlBAAAGCCEgIAAExQQgAAgAlKCAAAMEEJAQAAJighAADA\nBCUEAACYoIQAAAATlBAAAGCCEgIAAExQQgAAgAlKCAAAMEEJAQAAJighAADABCUEAACYoIQAAAAT\nlBAAAGCCEgIAAExQQgAAgAlKCAAAMEEJAQAAJighAADABCUEAACYoIQAAAATzaKEFBYW6qGHHtLT\nTz9tHQUAADQSx5eQjz/+WPPmzVOPHj2sowAAgEbk+BLi8XiUk5OjuLg46ygAAKARhVgHuJ4xY8ZY\nRwAAAE3A8SXEH2fOnFF1dbWGDx9uHQUAAJ/IyEi9//771jHMmS/H5OXlKTo6WjExMb6v2u+3bt3q\n189u166dQkJadM8CAKDZMh+hk5OTlZyc3CQ/e//+/U3ycwEAgP/MZ0IAAEBwajYlxOv1WkcAAACN\nyOV1+Oj+yCOP6NSpU6qurlZNTY1CQkLkcrmUn5+vyMhI63gAAOAWOb6EAACAlqnZLMcAAICWhRIC\nAABMUEIAAIAJSggAADBBCQEAACaCooRUVlZq4cKFSkpKUmJiolJTU3X69GnrWCZKSko0c+ZMJSQk\naNiwYVq9erV1JMcoLS3V3LlzlZCQoKSkJL3wwguqqqqyjuUoK1asUHR0tHUMR9m4caOSkpIUHx+v\nqVOnqqSkxDqSuaNHj2rSpEkaMGCAkpKSlJ6eLrfbbR3LxJdffqkHHnhACxYsqHdux44dSk5O1n33\n3acxY8boq6++MkhoKyhKSEZGhtxut7Zv366CggJ5PB4tWrTIOpaJ1NRUdevWTbt27VJWVpY+++wz\nZWVlWcdyhFmzZik8PFy7d+/WRx99pB9//FGrVq2yjuUYR44cUW5urlwul3UUx8jOzta2bduUnZ2t\nPXv2qFevXkH//6mmpkYpKSmKj4/X3r17tX37drndbi1btsw6WsC9/fbbWrFihXr06FHv3JEjR5SR\nkaH09HR98803mjx5subOnauysrLABzUUFCUkMjJSCxcuVHh4uMLDwzV+/HgdOHDAOlbAFRYW6tix\nY0pPT1doaKi6d++uKVOmKCcnxzqauT///FN9+/bVggUL1L59e0VERGjUqFHat2+fdTRH8Hq9Wrp0\nqaZOnWodxVHeffddPffcc7r77rsVGhqqzMxMZWZmWscydebMGf32229KTk5WSEiIwsPDNWLECB05\ncsQ6WsC1b99eH374obp3717v3JYtWzRkyBANHjxYbdu21RNPPKF77rlHeXl5BkntBEUJefHFF9W7\nd2/f96WlpbrzzjsNE9koKipSVFSUwsLCfMdiY2N1/PhxnTt3zjCZvdtvv13Lly9Xly5dfMdKS0sV\nERFhmMo5PvjgA7Vr106PP/64dRTHKCsr08mTJ1VZWanHHntMCQkJmjdvXtAuO9SKiIhQbGyscnJy\n9Ndff6m8vFwFBQUaOnSodbSAe+aZZ+q83l7p8OHDio2NrXMsNjZWhYWFgYjmGEFRQq508uRJrVu3\nTnPmzLGOEnCVlZXq2LFjnWOdOnXyncNlhYWFys7O1uzZs62jmPv999+1YcMGLV261DqKo9ROmxcU\nFOi9995TXl6eysrKtGTJEuNktlwul9auXaudO3eqf//+SkpKUk1NjZ5//nnraI5SUVFR7/U4PDxc\nFRUVRolstIgSkpeXp+joaMXExPi+ar/funWr73HFxcWaOHGiRo8erdGjRxsmdo7ad+1nnf+yAwcO\naPr06UpPT1diYqJ1HHMrV67U2LFj1bNnT+sojlL7fyclJUVdu3ZVRESEUlNTtWvXLnk8HuN0djwe\nj2bPnq1HH31U+/fv1xdffKGwsLAGN2aiLq/XG3SvxSHWARpDcnKykpOTr/mYQ4cOacaMGZo2bZpS\nUlIClMxZunTpUq9lnz17Vi6XS507dzZK5Syff/650tPTtWTJkuv+TQWDvXv36rvvvtMrr7wiiU+z\nvlLXrl0lXVzKqxUVFSWv1yu3261u3bpZRTO1d+9elZSU+GY+QkNDlZqaqpEjR+qPP/6od/UfrK72\nenzlknAwaBEzIdfz888/a+bMmcrIyAjaAiJJffr0UWlpaZ2ll0OHDqlXr17q0KGDYTJnOHjwoDIy\nMrR+/XoKyCV5eXlyu90aMmSIEhMTNWbMGHm9Xg0aNEg7duywjmeqW7duCgsLq7Ph8uTJkwoJCdFd\nd91lmMxWTU2N76uWx+MJuiv86+nTp48OHz5c51hhYaH69etnlMhGUJSQZcuWady4cRo5cqR1FFMx\nMTGKi4vTmjVrVFVVpeLiYmVlZWnChAnW0cxVV1dr8eLFSktL06BBg6zjOMaiRYuUn5+v3Nxc5ebm\navPmzZKk3NxcDR8+3DidrdatW2vs2LHatGmTfv31V5WXl+utt97Sk08+qVatguKltUHx8fG67bbb\ntG7dOv3999+qqKjQpk2bNGDAAGZBrjBu3Dh9/fXX2r17tzwej7Zs2aJffvkl6C6AXN4WPr96+vRp\nDR06VG3atJF0ce9D7brbO++8o/vvv984YWCVlZVp8eLF+vbbbxUWFqbx48fr2WeftY5lbv/+/Zo4\ncaLatm3r+/uo/Tc/P1+RkZHWER2hpKREDz74YFDebtkQj8ejVatWadu2bbpw4YIefvhhLV68OOhn\nFouKirRy5Ur98MMPatOmjRISEpSRkRF0dyXGxcXJ5XLpwoULki4WV5fLpe+//16StHPnTr3++us6\ndeqUevfurczMTPXv398ycsC1+BICAACcKXjnDAEAgClKCAAAMEEJAQAAJighAADABCUEAACYoIQA\nAAATlBAAAGCCEgIAAExQQgAAgAlKCAAAMEEJASBJqqio0NChQ/XSSy/VO5eTk6O4uDjfZ8a43W7N\nnz9f0dHR2rNnT6CjAmghKCEAJEmdO3fWm2++qS1btqigoMB3vLi4WK+++qoyMzMVExOjgwcPauTI\nkQoPD+fj2QH4hRICwKdfv35KS0tTZmamTpw4ofPnz2vBggUaPny4nnrqKUlSeXm5NmzYoBkzZojP\nvwTgjxDrAACcZdKkSTp48KDmz5+v+Ph4/fPPP3r55Zd950eMGCFJKikpsYoIoIVgJgRAPcuXL1dF\nRYWys7P1xhtvqEOHDtaRALRAlBAA9fz0009yu92644479Omnn1rHAdBCsRwDoI7aO1/mzJmje++9\nV1OnTtXAgQOVmJhoHQ1AC8NMCAAfr9ertLQ09ezZUzNmzNDAgQM1bdo0paWlye12W8cD0MJQQgD4\nrF+/XkePHtVrr73mOzZv3jxFRUUpLS2tzmO5MwaAv1xeXkkASNqzZ49mzZqljRs3avDgwXXOnThx\nQqNGjdL06dO1b98+7du3T5J0/vx5hYSEyOVyKSoqSp988olFdADNFCUEAACYYDkGAACYoIQAAAAT\nlBAAAGCCEgIAAExQQgAAgAlKCAAAMEEJAQAAJighAADABCUEAACYoIQAAAATlBAAAGCCEgIAAEz8\nPzxqT45q9Dp8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe4f4742d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot('X1', 'X2', hue='C', data=data_with_c, fit_reg=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# calculate the cost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.79417636337158704"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "km.cost(data2, final_centroid, final_C)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# k-mean with multiple tries of randome init, pick the best one with least cost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "best_C, best_centroids, least_cost = km.k_means(data2, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.79417636337158704"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "least_cost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7fe4f46c2128>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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EZAmGECIiIrIEQwgRERFZgiGEiIiILMEQQkRERJZgCCEiIiJLMIQQERGRJRhC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\nPzxqT45q9Dp8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe4f46c2a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_with_c = km.combine_data_C(data2, best_C)\n",
    "sns.lmplot('X1', 'X2', hue='C', data=data_with_c, fit_reg=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# try sklearn kmeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sk_kmeans = KMeans(n_clusters=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(copy_x=True, init='k-means++', max_iter=300, n_clusters=3, n_init=10,\n",
       "    n_jobs=1, precompute_distances='auto', random_state=None, tol=0.0001,\n",
       "    verbose=0)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sk_kmeans.fit(data2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sk_C = sk_kmeans.predict(data2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7fe4f03a9128>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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swRBCRERElmAIISIiIkswhBAREZElGEKIiIjIEgwhREREZAmGECIiIrIEQwgR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\ncCHZxt0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe4f03a92e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_with_c = km.combine_data_C(data2, sk_C)\n",
    "sns.lmplot('X1', 'X2', hue='C', data=data_with_c, fit_reg=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
